Method for researching cross-seasonal relation of rainfall abnormity in spring and summer of middle America

Abstract

The invention discloses a method for researching the cross-seasonal relation of rainfall abnormity in spring and summer in the middle and America, and the method comprises the steps: downloading a data set, and processing the data set to retain interannual signals; calculating Chinese American rainfall indexes in spring and summer by using the data; calculating a precipitation level phase transition index to obtain a transition type event and a persistent type event; further dividing the transition event and the persistent event into a positive event and a negative event; the physical mechanism of rainfall anomaly in the middle and American regions in spring and summer during the occurrence period of transformation and persistent events is studied; identifying and exploring the physical process of the sea temperature key area influencing rainfall anomaly in spring and summer; and exploring precursor factors influencing the cross-seasonal relationship of rainfall anomalies in spring and summer. The method solves the problem that in the prior art, cross-season continuous rainfall abnormity in the middle and American regions is not involved. According to the method, the precursor factors of the persistent events and the transformed events are identified, and the method has the potential to be applied to rainfall forecast in the middle and American regions, and provides reference for disaster prevention and reduction and agricultural production.

Description

Technical Field

[0001] This invention relates to a method for studying precipitation anomalies in Central America, specifically a method for studying the cross-seasonal relationship of spring and summer precipitation anomalies in Central America. Background Technology

[0002] Central America (CA) is a climate change sensitive region, as documented in existing literature 1 (Magaña, V., Amador, JA, & Medina, S. The midsummer drought over Mexico and Central America). J. Clim. Reference 12, 1577-1588 (1999) indicates that Central America is severely affected by abnormal precipitation and drought. Reference 2 (He, C., Li, T., & Zhou, W. Drier North American monsoon in contrast to Asian–African monsoon under global warming) points out that the Central American region is severely affected by abnormal precipitation and drought. J. Climate Reference 33, 9801-9816 (2020) indicates that precipitation in the region is expected to decrease against the backdrop of global warming, which will further exacerbate the negative impact of precipitation changes on local production and living activities. Reference 3 (Alfaro, EJ, Chourio, X., Muñoz, Á. G., & Mason, SJ Improved seasonal prediction skill of rainfall for the Primera season in Central America) Int. J. Climatol. (38, e255-e268 (2018)) points out that since the main growing season for food in Central America is from April to September, from the perspective of food production, the precipitation variability in Central America during spring and summer will also have an impact on local production and life.

[0003] There is also document 4 (Steinhoff, DF, Monaghan, AJ, & Clark, MP Projected impact of twenty-first century ENSO changes on rainfall over Central America and northwest South America from CMIP5 AOGCMs. Clim. Dyn.(44, 1329-1349 (2015)) points out that since precipitation in Central America is mainly concentrated in the summer, existing technologies mainly focus on the variability of summer precipitation in the region and do not cover continuous precipitation anomalies across seasons. Compared with single-season precipitation anomalies, continuous precipitation anomalies across seasons often have a greater impact on local agricultural production activities.

[0004] Therefore, it is necessary to study the cross-seasonal relationships of spring and summer precipitation anomalies in Central America, as well as the physical mechanisms and precursor signals behind these cross-seasonal relationships, in order to make relatively accurate predictions of spring and summer precipitation in Central America and thus provide a reference for local agricultural production activities. Summary of the Invention

[0005] The purpose of this invention is to provide a method for studying the cross-seasonal relationship of spring and summer precipitation anomalies in Central America. This method solves the problem that existing technologies do not address the persistent cross-seasonal precipitation anomalies in Central America. It aims to study the cross-seasonal relationship of spring and summer precipitation anomalies in Central America and the physical mechanisms behind these cross-seasonal relationships, thereby making relatively accurate predictions of spring and summer precipitation in Central America and providing a reference for local agricultural production activities.

[0006] To achieve the above objectives, this invention provides a method for studying the cross-seasonal relationship of spring and summer precipitation anomalies in Central America, the method comprising: Step 1: Download the monthly reanalysis global atmospheric circulation data provided by ERA5 and the sea surface temperature reanalysis dataset provided by ERSST V5. All datasets have been processed to preserve interannual signals. Step 2: Calculate the spring and summer Central American precipitation index using monthly reanalysis global atmospheric circulation data provided by ERA5; The Central America Precipitation Index is defined as the average precipitation anomaly in the region of 7°N-22.5°N and 80°W-100°W.

[0007] Step 3: Calculate the precipitation phase transition index from the precipitation index to obtain the transitional and persistent events; The classification of transitional and persistent events is based on the precipitation transition index, which categorizes spring and summer precipitation anomalies in Central America into transitional and persistent events. Step 4: Based on the precipitation index, classify transitional events into positive and negative events; classify persistent events into positive and negative events.

[0008] Step 5: Use the water vapor budget equation to study the physical mechanisms of precipitation anomalies in Central America during the spring and summer seasons of transitional and persistent events; Step 6: Use synthetic analysis to identify key sea surface temperature (SST) zones that regulate precipitation in Central America, and define SST indices based on these key SST zones.

[0009] Step 7: Use the sea surface temperature index combined with correlation analysis and partial correlation analysis to explore the role of sea surface temperature anomaly evolution in regulating precipitation anomalies in Central America during spring and summer.

[0010] Step 8: Use regression analysis to explore the physical processes by which key sea surface temperature zones influence abnormal precipitation in Central America during spring and summer. Step 9: Use synthetic analysis to explore the precursor factors influencing the transseasonal relationship of abnormal precipitation in Central America during spring and summer.

[0011] Preferably, in step one, the monthly reanalysis global atmospheric circulation data provided by ERA5 includes average evaporation rate, average total precipitation rate, zonal wind, meridional wind, vertical velocity, and specific humidity data; the download address for the monthly reanalysis global atmospheric circulation data provided by ERA5 is: https: / / cds.climate.copernicus.eu / datasets; the download address for the sea surface temperature reanalysis dataset provided by ERSST V5 is: https: / / www1.ncdc.noaa.gov / pub / data / cmb / ersst / v5 / netcdf / .

[0012] Preferably, in step two, the present invention uses monthly reanalysis global atmospheric circulation data provided by ERA5 to calculate the precipitation index of Central America in spring and summer; spring refers to March to May, and summer refers to June to September.

[0013] Preferably, in step three, the formula for calculating the precipitation phase transition index is: Precipitation Phase Transition Index = Cor all -Cor Rem (t) (1; In formula (1), Cor all To investigate the correlation between the spring and summer precipitation indices in Central America during the event period; Cor Rem (t) is defined as the correlation coefficient between the Central American precipitation index in spring and summer after year t, without considering the correlation coefficient between the two.

[0014] Preferably, in step three, the determination of transitional events and persistent events is based on the numerical value of the precipitation phase transition index, which classifies spring and summer precipitation anomalies in Central America into transitional events and persistent events. The persistent event is an event with a precipitation phase transition index greater than 0; the transitional event is an event with a precipitation phase transition index less than 0. During persistent events, the spring and summer precipitation indices in Central America show a positive correlation; while during transitional events, the spring and summer precipitation indices in Central America show a negative correlation.

[0015] Preferably, in step four, the positive event refers to an event in which the precipitation index in Central America is greater than 0 in spring; the negative event refers to an event in which the precipitation index in Central America is less than 0 in spring; the evolution of the transitional event and the persistent event is related to the evolution of the vertically integrated water vapor flux and vertical velocity.

[0016] Preferably, in step five, the expression for the water vapor budget equation is: (2); In formula (2), The outlier represents the precipitation. This represents the contribution of local evaporation to precipitation anomalies. Represents the horizontal thermal term, Represents the horizontal dynamic term. Represents the vertical thermal term. This represents a nonlinear term. Specifically, Representing the vertical dynamic term, its physical meaning is: the vertical transport of climatological relative humidity caused by abnormal vertical motion. Outliers representing vertical velocity The climatological average of vertical velocity over the study period is represented by NL; NL represents the nonlinear term; <> means: , representing the vertical integral from the Earth's surface (Ps=1000 hPa) to the tropopause (Pt=300 hPa), and g representing gravitational acceleration, chosen as 9.8 m / s². 2 ; The climatological average value of the horizontal wind field during the study period; This represents anomalies in the horizontal wind field relative to the climatological state. The horizontal gradient representing relative humidity relative to climatological anomalies; The horizontal gradient representing the climatological average of relative humidity; The vertical gradient representing the climatological average relative humidity; This represents the vertical gradient of relative humidity relative to climatological anomalies.

[0017] Preferably, in step six, the key sea surface temperature region is the tropical central and eastern Pacific Ocean and the tropical North Atlantic Ocean; the method further includes: using synthetic analysis to reveal the key tropical ocean sea surface temperature anomaly regions that regulate spring and summer precipitation anomalies in Central America during persistent and transitional events, and defining a sea surface temperature index based on the key sea surface temperature anomaly regions.

[0018] Preferably, in step seven, the method includes: based on the defined sea surface temperature index, combined with correlation analysis and partial correlation analysis, revealing the impact of tropical ocean sea surface temperature anomalies on precipitation anomalies in Central America.

[0019] Preferably, in step eight, the method includes: based on the defined key sea surface temperature zones and combined with regression analysis, revealing the physical processes by which tropical ocean sea surface temperature anomalies affect precipitation anomalies in Central America.

[0020] Preferably, in step nine, the method includes: using synthetic analysis to reveal tropical ocean surface temperature anomalies during winter prior to transitional and persistent events.

[0021] Preferably, in step nine, the regions in which the winter sea surface temperature anomalies before the occurrence of transitional and persistent events obtained from the synthetic analysis pass the 90% significance test can be identified as precursor factors for these two types of events.

[0022] This invention provides a method for studying the cross-seasonal relationship of spring and summer precipitation anomalies in Central America, which solves the problem that existing technologies do not address the issue of continuous cross-seasonal precipitation anomalies in Central America, and has the following advantages: 1. This invention proposes a method for studying the cross-seasonal relationship of spring and summer precipitation anomalies in Central America. The calculation method is very simple and can be further applied to the study of precipitation persistence in other regions of the world.

[0023] 2. The physical mechanisms behind precipitation in Central America during transitional and persistent events were explored, the contributions of various precipitation-related physical processes to precipitation in Central America were quantitatively diagnosed, and the effects of tropical ocean surface temperature on precipitation in Central America during different types of events were distinguished.

[0024] 3. This invention identifies precursor factors for persistent and transformative events, which have the potential to be applied to precipitation forecasting in Central America, thereby providing a reference for disaster prevention and mitigation and agricultural production. Attached Figure Description

[0025] Figure 1 This is a graph showing the precipitation index and its correlation coefficient in Central America during spring and summer from 1980 to 2023.

[0026] Figure 2 This is a precipitation phase transition index diagram for the period 1980-2023 of this invention.

[0027] Figure 3 This is a map showing precipitation anomalies in Central America during the spring and summer of 2010.

[0028] Figure 4 This invention synthesizes and analyzes precipitation anomalies in Central America during spring to summer, resulting in transitional and persistent events.

[0029] Figure 5 This diagram illustrates the impact of various terms in the water vapor budget equation during transitional and persistent events on precipitation anomalies in Central America, as presented in this invention.

[0030] Figure 6 This invention provides a synthetic analysis revealing the evolution characteristics of tropical ocean sea surface temperature and 925 hPa wind field during transitional and persistent events.

[0031] Figure 7 This invention presents a diagram illustrating the physical processes by which tropical ocean sea surface temperature regulates precipitation in Central America, based on the water vapor budget equation and regression analysis.

[0032] Figure 8 This invention discloses a precursor factor diagram for the occurrence of transformative and persistent events.

[0033] Figure 9 This refers to the precipitation phase transition index calculated based on different study time periods.

[0034] Figure 10 This is a flowchart illustrating the method for studying the cross-seasonal relationship of abnormal spring and summer precipitation in Central America according to the present invention. Detailed Implementation

[0035] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Example 1: A method for studying the transseasonal relationship of spring and summer precipitation anomalies in Central America, such as Figure 8 The diagram shows a flowchart of the method for studying the cross-seasonal relationship of spring and summer precipitation anomalies in Central America according to the present invention. The method includes: Step 1: Download the monthly reanalysis global atmospheric circulation data provided by ERA5 and the sea surface temperature reanalysis dataset provided by ERSST V5. All datasets have been processed to preserve interannual signals.

[0037] This invention uses ERA5 monthly averaged data on single levels from 1940 to present to provide the mean evaporation rate and mean total precipitation rate. The units for mean evaporation rate and mean total precipitation rate are kg / m³. -2 s -1 The unified unit is converted to: (mm day) -1Furthermore, this invention also utilizes ERA5 monthly averaged data on pressure levels from 1940 to the present, providing data on zonal (U-component of wind), meridional (V-component of wind), vertical velocity, and specific humidity. The units for zonal and meridional wind data are milliseconds (ms). -1 The unit of vertical velocity is Pa·s. -1 The unit for specific humidity data is kg / kg; this will be converted to g / kg. The unit for sea surface temperature data provided by ERSST V5 is °C. To obtain interannual signals, all data have had the climatological period from 1980 to 2023 removed and have undergone detrending and 9-year high-pass filtering. The download address for the monthly reanalysis global atmospheric circulation data provided by ERA5 is: https: / / cds.climate.copernicus.eu / datasets; the download address for the ERSST V5 dataset is: https: / / www1.ncdc.noaa.gov / pub / data / cmb / ersst / v5 / netcdf / .

[0038] Step 2: Calculate the spring and summer precipitation index of Central America using monthly reanalysis global atmospheric circulation data provided by ERA5.

[0039] The Central American Precipitation Index (CPI) is defined using regional average environmental field anomalies. The CPI is the average precipitation anomaly within the region of 7°N–22.5°N and 80°W–100°W. This invention uses monthly reanalysis global atmospheric circulation data provided by ERA5 to calculate the CPI for spring (March–May) and summer (June–September) from 1980 to 2023. Reference 5 (Luo, W., Weng, J., Luo, J., & Wang, L. Interannual Covariation of the North American and African Summer Monsoons. Int. J. Climatol., 44, 5500-5519 (2024).) also provides a method for calculating the correlation coefficient and a test formula.

[0040] like Figure 1 As shown, this invention presents a graph illustrating the spring and summer precipitation indices and their correlation coefficients in Central America during the period 1980-2023. (Source: [Insert graph here]) Figure 1It can be seen that there is a positive correlation between the spring precipitation index and the summer precipitation index in Central America (r=0.40, p<0.1), which indicates that the abnormal precipitation in Central America in spring can continue into summer.

[0041] Step 3: Calculate the precipitation phase transition index from the precipitation index to obtain the transitional event and the persistent event.

[0042] In step two, this invention calculates the precipitation phase transition index using the precipitation index, and based on the value of the precipitation phase transition index, classifies spring and summer precipitation anomalies in Central America into transitional events and persistent events. Reference 5 provides a method for calculating the correlation coefficient; based on this method, this invention proposes a precipitation phase transition index. The formula for calculating the precipitation phase transition index is as follows:

[0043] Precipitation phase transition index = Cor all -Cor Rem (t) (1; Among them, Cor all To study the correlation coefficient between the spring and summer precipitation indices in Central America within the event period; Cor Rem (t) is defined as the correlation coefficient between the precipitation phase transition index in Central America during spring and summer after year t, without considering the correlation between the two. It is assumed that in year t, the larger the value of the precipitation phase transition index, the better the persistence of precipitation in Central America during spring and summer of that year; conversely, the worse the persistence.

[0044] The event period of interest in this invention is 1980-2023. Therefore, in formula (1), Cor all The correlation coefficient between the spring and summer precipitation indices of Central America during the period 1980–2023 was calculated; Cor Rem (t) is defined as the correlation coefficient between the spring and summer precipitation indices of Central America after year t, without considering the correlation between these indices. For example, when calculating the phase transition index in 1980, i.e., at t=1980, Cor Rem (t) represents the correlation coefficient of the Central American precipitation index for spring and summer after 1980 (i.e., 1981-2023).

[0045] like Figure 2 As shown in the diagram, this invention presents a precipitation phase transition index map for the period 1980-2023, where red dots represent selected transition events and blue dots represent selected persistent events. The precipitation phase index values ​​can effectively indicate the relationship between spring and summer precipitation anomalies in Central America. For example, the precipitation phase index was highest in 2010, indicating that spring precipitation anomalies in Central America that year could be well sustained into the summer. Figure 3The study further illustrates the precipitation anomalies in Central America during the spring and summer of 2010, showing increased precipitation in both seasons, consistent with the results revealed by the precipitation phase transition index defined in this patent.

[0046] Of the precipitation phase transition indices from 1980 to 2023, 14 years had an indices greater than 0 (blue dots in the figure). These 14 years were selected to define "persistent events." Correspondingly, the 14 years with the smallest precipitation phase transition indices were defined as "transitional events" (red dots in the figure). During persistent and transitional events, spring and summer precipitation anomalies in Central America exhibited different transseasonal relationships. During persistent events, spring and summer precipitation indices in Central America showed a positive correlation (r=0.95, p<0.01), while during transitional events, spring and summer precipitation indices in Central America showed a negative correlation (r=-0.63, p<0.01).

[0047] Step 4: Based on the precipitation index, transforming events are classified into positive and negative events, and persistent events are also classified into positive and negative events.

[0048] This invention uses positive and negative events for synthetic analysis to obtain precipitation anomalies in Central America from spring to summer during transitional and persistent events. Reference 5 mentioned above states that the seasonal evolution of precipitation during the two types of events is closely related to water vapor flux and the vertical velocity in the lower troposphere (i.e., 700 hPa), as well as the calculation formula for water vapor flux and the calculation formula and verification method based on synthetic analysis of positive and negative events.

[0049] A spring Central American precipitation index greater than 0 is defined as a "positive event," while a spring Central American precipitation index less than 0 is defined as a "negative event." Composite analysis is used to obtain the differences between positive and negative events to reveal the characteristics of precipitation and circulation during transitional and persistent events.

[0050] like Figure 4 As shown, this invention synthesizes and analyzes precipitation anomalies in Central America from spring to summer during transitional and persistent events. The color-coded values ​​represent precipitation (mm / day). -1 Water vapor flux (arrow, kg m) -1 s -1 ) and a vertical velocity of 700 hPa (fill in, Pa s) -1 The dotted areas represent regions that passed the 90% significance test; the red box represents the Central American region of interest. Figure 4 It can be seen that during transitional events, positive precipitation anomalies exist in Central America during the spring, and these anomalies change sign to negative in the summer. However, for persistent events, positive precipitation anomalies exist in Central America from spring to summer.

[0051] The difference in precipitation anomalous evolution during positive and negative events is related to the evolution of vertically integrated water vapor flux and mid-tropospheric (700 hPa) vertical velocity. During the transitional event spring, Central America experiences anomalous upward motion and water vapor convergence, favoring increased precipitation. However, in the following summer, Central America is affected by downward motion and water vapor divergence, which reduces precipitation. Conversely, during the persistent event spring, Central America is influenced by anomalous upward motion and water vapor convergence. These favorable large-scale environmental conditions persist from spring into summer.

[0052] Step 5: Use the water vapor budget equation to study the physical mechanisms of precipitation anomalies in Central America during the spring and summer seasons of transitional and persistent events.

[0053] This invention explores the influence of dynamic and thermodynamic factors on precipitation in Central America during different types of events based on the water vapor budget equation.

[0054] The expression for the water vapor budget equation is: (2); In formula (2), The outlier represents the precipitation. This represents the contribution of local evaporation to precipitation anomalies. Represents the horizontal thermal term, Represents the horizontal dynamic term. NL represents the vertical thermal term, and NL represents the nonlinear term. Specifically, This represents the vertical dynamic term, whose physical meaning is the vertical transport of climatological relative humidity caused by abnormal vertical motion. Among them, Outliers representing vertical velocity The climatological average value of vertical velocity during the study period; The vertical gradient representing the climatological average relative humidity; This represents the vertical gradient of relative humidity relative to climatological anomalies; <> is: , representing the vertical integral from the Earth's surface (Ps=1000 hPa) to the tropopause (Pt=300 hPa); g represents the gravitational acceleration, chosen as 9.8 m / s². 2 ; The climatological average value of the horizontal wind field during the study period; This represents anomalies in the horizontal wind field relative to the climatological state. The horizontal gradient representing relative humidity relative to climatological anomalies; The horizontal gradient represents the climatological average relative humidity.

[0055] likeFigure 5 As shown in the figure, this invention provides a synthetic analysis to diagnose the impact of various terms in the water vapor budget equation on precipitation anomalies in Central America during transitional and persistent events. The diagonal lines in the figure represent values ​​obtained from the synthetic analysis that pass the 90% significance test. Figure 5 It can be seen that, in terms of both transitional and persistent events, precipitation anomalies in Central America during spring and summer are influenced by dynamic factors (especially...). ) regulation.

[0056] Step 6: Use synthetic analysis to identify key sea surface temperature (SST) zones that regulate precipitation in Central America, and define SST indices based on these key SST zones.

[0057] This invention uses synthetic analysis to identify key sea surface temperature (SST) zones in Central America that regulate abnormal precipitation during spring and summer, and defines a SST index based on the regional average SST anomaly of these key SST zones.

[0058] like Figure 6 As shown, the synthetic analysis of this invention reveals the evolution characteristics of tropical ocean sea surface temperature (SST) and 925 hPa wind field during transitional and persistent events. Tropical ocean SST is represented by color (°C), and 925 hPa wind field is represented by arrows (m / s). Dotted signals in the figure represent SST anomalies obtained from the synthetic analysis that passed the 90% significance test; wind field anomalies shown in the figure only indicate signals that passed the 90% significance test. Figure 6 It is known that during the spring of transitional events, there are abnormally cold sea surface temperatures in the central and eastern tropical Pacific, which transform into warm sea surface temperatures in the summer. Simultaneously, there are persistent cold sea surface temperature anomalies over the tropical Atlantic from spring to summer. During the spring of persistent events, the tropical Atlantic experiences warm sea surface temperatures, while the signal over the central and eastern tropical Pacific is relatively weak, generally failing to pass the 90% significance test. Entering summer, the signal over the tropical Atlantic disappears, replaced by cold sea surface temperature anomalies in the central and eastern tropical Pacific.

[0059] Along with the seasonal evolution of sea surface temperature anomalies in the tropical central and eastern Pacific and the tropical Atlantic, atmospheric wind fields exhibit seasonal changes. During the transitional events of spring, anomalous cyclonic circulation exists over Central America, which favors water vapor convergence and local upward motion. However, in the following summer, the cyclonic circulation over Central America transforms into anticyclonic circulation, which enhances local divergence and subsidence. In contrast, during persistent events, the lower atmosphere over Central America is influenced by anomalous cyclonic circulation from spring to summer, which favors sustained local convergence and upward motion.

[0060] These results indicate a close link between transitional and persistent events and the evolution of sea surface temperatures (SST) in the tropical central and eastern Pacific and the tropical North Atlantic. Based on the results of the synthetic analysis, two key SST regions can be identified: the tropical central and eastern Pacific (3°S-3°N, 170°W-120°W) and the tropical North Atlantic (0°-20°N, 30°W-80°W). According to reference 5, different tropical ocean SST indices can be defined based on regionally averaged SST anomalies. This invention further defines the tropical central and eastern Pacific SST index and the tropical North Atlantic SST index using the averaged SST anomalies of the identified key SST regions. The tropical central and eastern Pacific SST index is defined as the regionally averaged SST anomaly of the tropical central and eastern Pacific (3°S-3°N, 170°W-120°W), and the tropical North Atlantic SST index is defined as the regionally averaged SST anomaly of the tropical North Atlantic (0°-20°N, 30°W-80°W). According to reference 5, the method for defining tropical ocean SST indices based on regionally averaged SST anomalies is as follows: (3); In formula (3), lon1 and lon2 represent the longitudes spanned by the key sea surface temperature zone, lat1 and lat2 represent the latitudes spanned by the key sea surface temperature zone, area (x,y)dxdy represents the actual area corresponding to the grid point with longitude x and latitude y, and SSTA(x,y) represents the sea surface temperature anomaly. Specifically, when calculating the sea surface temperature index of the tropical central and eastern Pacific, lon1 in formula (3) is taken as 170°W, lon2 as 120°W, lat1 as 3°S, and lat2 as 3°N. However, when calculating the sea surface temperature index of the tropical North Atlantic, lon1 is taken as 30°W, lon2 as 80°W, lat1 as 0°N, and lat2 as 20°N.

[0061] Step 7: Use the sea surface temperature index combined with correlation analysis and partial correlation analysis to explore the role of sea surface temperature anomaly evolution in regulating precipitation anomalies in Central America during spring and summer.

[0062] This invention applies reference 6 (Wang, X., Tan, W., & Wang, C. A new index for identifying different types of El Niño Modoki events). Clim. Dyn. Correlation analysis was conducted using partial correlation analysis and significance testing in ,50, 2753-2765(2018) to reveal a close relationship between the sea surface temperature anomaly index in the tropical central and eastern Pacific and the tropical North Atlantic and precipitation in Central America during the same period. The results are detailed in Table 1.

[0063] Table 1. Relationship between Central American precipitation index and concurrent tropical ocean surface temperature index during transitional and persistent events.

[0064] Note: The area outside the parentheses represents the correlation between the Central American Precipitation Index and the Tropical Central and Eastern Pacific Sea Surface Temperature Index; the area inside the parentheses represents the correlation between the Central American Precipitation Index and the Tropical Atlantic Sea Surface Temperature Index; the asterisk indicates that the correlation has passed the 90% significance test.

[0065] Table 1 shows that during the transition event, the spring precipitation index of Central America was significantly negatively correlated with the concurrent sea surface temperature anomalies in the tropical Pacific and tropical Atlantic, with correlation coefficients of -0.72 and -0.47, respectively, both passing the 90% significance test. In the following summer, the negative correlation between the tropical Central America precipitation index and the concurrent tropical Pacific sea surface temperature anomaly index remained significant (r = -0.82, p < 0.1), while the correlation between the Central America precipitation index and the concurrent tropical Atlantic sea surface temperature anomaly index turned positive (r = 0.70, p < 0.1). These results indicate that sea surface temperatures in the central and eastern tropical Pacific and the tropical Atlantic may have played a role in regulating concurrent precipitation in Central America during the transition event.

[0066] In contrast, during the spring of persistent events, the Central American precipitation index showed a close correlation with the concurrent tropical Atlantic sea surface temperature (SST) (r=0.54, p<0.1), while the correlation with the tropical central and eastern Pacific SST anomaly index was weaker (r=-0.17, p>0.1). In the following summer, the correlation between the Central American precipitation index and the concurrent tropical Atlantic SST anomaly weakened and disappeared (r=0.43, p>0.1), while the correlation with the concurrent tropical central and eastern Pacific cold SST anomaly strengthened (r=-0.72, p<0.1). Therefore, during persistent events, spring precipitation anomalies in Central America are influenced by warm tropical Atlantic SST anomalies, while summer precipitation anomalies are modulated by cold tropical central and eastern Pacific SST anomalies.

[0067] Partial correlation analysis was used to further examine the role of sea surface temperature in the tropical central and eastern Pacific and tropical North Atlantic during the transition event, as detailed in Table 2.

[0068] Table 2. Partial correlation analysis diagnoses the role of sea surface temperatures in the tropical central and eastern Pacific and tropical North Atlantic on the precipitation index in Central America during transitional events.

[0069] Note: An asterisk indicates that the significance test passed by 90%.

[0070] Table 2 shows that after controlling for the influence of spring tropical North Atlantic sea surface temperature (SST), the partial correlation coefficient between spring Central American precipitation and the concurrent tropical central and eastern Pacific SST index was -0.62 (p<0.1). Similarly, after controlling for the effect of summer tropical North Atlantic SST anomaly index, the association between summer Central American precipitation and the concurrent tropical central and eastern Pacific SST index remained significant (r=0.72, p<0.1). In contrast, after removing the tropical central and eastern Pacific SST anomaly, the association between the tropical North Atlantic SST anomaly index and the Central American precipitation index became insignificant, failing the 90% significance test. Therefore, during the transition event, spring and summer Central American precipitation anomalies were modulated by concurrent tropical central and eastern Pacific SST anomalies.

[0071] Step 8: Use regression analysis to explore the physical processes by which key sea surface temperature zones influence abnormal precipitation in Central America during spring and summer. Based on the tropical central and eastern Pacific Sea Surface Temperature (SST) index and the tropical Atlantic Sea Surface Temperature (SST) index defined in step six, this invention applies regression analysis and its testing methods from reference 5 to reveal the physical processes by which SST anomalies in key tropical Pacific and tropical Atlantic SST regions influence abnormal precipitation in Central America during spring and summer. Generally, when the SST anomaly index is greater than 0, it indicates the presence of warm SST anomalies in the region. Therefore, the results of the regression analysis can reflect the impact of warm SST anomalies on precipitation in Central America and related large-scale environmental fields.

[0072] like Figure 7 As shown, this invention reveals a diagram illustrating the physical processes by which tropical ocean sea surface temperature regulates precipitation in Central America, based on the water vapor budget equation and regression analysis. Figure 7 It is known that during transitional and persistent events, tropical ocean surface temperature anomalies mainly regulate dynamic factors (especially...) This influences precipitation anomalies in Central America. However, sea surface temperature anomalies in the tropical central and eastern Pacific and the tropical Atlantic have a greater impact on dynamic factors (i.e., The effects vary. Warmer sea surface temperatures in the tropical central and eastern Pacific weaken the influence of [unclear - possibly referring to a specific weather system or phenomenon] over Central America. This leads to reduced precipitation. However, the warm sea surface temperature anomalies in the tropical Atlantic enhance the atmospheric conditions over Central America. This leads to increased precipitation.

[0073] Combination Figure 6 as well as Figure 7The analysis results show that during the spring of transitional events, cold sea surface temperature (SST) anomalies exist over the tropical central and eastern Pacific, which favors increased precipitation in Central America. In the following summer, these cold SST anomalies transition to warm SST anomalies, leading to decreased precipitation. These results indicate that the phase transition of cold SST in the tropical central and eastern Pacific during spring to summer during transitional events is unfavorable for the persistence of spring precipitation anomalies in Central America into summer. During persistent events, warm SST anomalies exist over the tropical Atlantic in spring, which favors increased precipitation in Central America. In the summer of persistent events, cold SST anomalies occur in the tropical central and eastern Pacific, which also favors increased precipitation in Central America. Therefore, the combined effect of Atlantic SST and tropical Pacific SST contributes to the persistence of spring precipitation anomalies in Central America into summer.

[0074] Step 9: Use synthetic analysis to explore the precursor factors influencing the transseasonal relationship of abnormal precipitation in Central America during spring and summer.

[0075] This invention uses synthetic analysis to reveal sea surface temperature anomalies in the tropical oceans during winter preceding transitional and persistent events, and the cross-seasonal relationship between sea surface temperature signals over the tropical central and eastern Pacific and the tropical Atlantic and spring and summer precipitation anomalies in Central America.

[0076] like Figure 8 As shown, this invention discloses a precursor factor diagram for transitional and persistent events. (From...) Figure 8 It can be seen that during the winter of transitional events, there are abnormally warm sea surface temperatures in the tropical central and eastern Pacific, while the anomalous signals over the tropical Atlantic fail to pass the 90% significance test; for persistent events, there are abnormally warm sea surface temperatures in the tropical Atlantic during the previous winter, while no signals passing the 90% significance test can be observed over the tropical central and eastern Pacific.

[0077] Therefore, sea surface temperature signals over the tropical central and eastern Pacific and the tropical Atlantic can serve as a precursor to forecasting abnormal precipitation in Central America during spring and summer.

[0078] Example 2: A method for studying the transseasonal relationship of spring and summer precipitation anomalies in Central America is basically the same as that in Example 1, except that: The precipitation phase transition index was compared between two time periods: 1980-2023 and 1940-2023.

[0079] like Figure 9As shown, the precipitation phase transition index was calculated based on different study time periods. The results indicate that the precipitation phase transition index calculated based on different time periods exhibits certain differences in amplitude, suggesting that the study time period has a certain impact on the results of the method of this invention. However, the precipitation phase transition indices defined based on different time periods show similar trends between 1980 and 2023, indicating that the precipitation phase transition indices defined based on different time periods can effectively capture the connection between spring and summer precipitation anomalies in Central America.

[0080] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A method for studying the transseasonal relationship of spring and summer precipitation anomalies in Central America, characterized in that, The method includes: Step 1: Download the monthly reanalysis global atmospheric circulation data provided by ERA5 and the sea surface temperature reanalysis dataset provided by ERSST V5. All datasets have been processed to preserve interannual signals. Step 2: Calculate the spring and summer Central American precipitation index using monthly reanalysis global atmospheric circulation data provided by ERA5; Step 3: Calculate the precipitation phase transition index from the precipitation index to obtain the transitional and persistent events; Step 4: Based on the precipitation index, classify transitional events into positive and negative events, and classify persistent events into positive and negative events; Step 5: Use the water vapor budget equation to study the physical mechanisms of precipitation anomalies in Central America during the spring and summer seasons of transitional and persistent events; Step 6: Use synthetic analysis to identify key sea surface temperature (SST) zones that regulate precipitation in Central America, and define SST indices based on these key SST zones; Step 7: Use the sea surface temperature index combined with correlation analysis and partial correlation analysis to explore the role of sea surface temperature anomaly evolution in regulating precipitation anomalies in Central America during spring and summer. Step 8: Use regression analysis to explore the physical processes by which key sea surface temperature zones influence abnormal precipitation in Central America during spring and summer. Step 9: Use synthetic analysis to explore the precursor factors influencing the transseasonal relationship of abnormal precipitation in Central America during spring and summer.

2. The method according to claim 1, characterized in that, In step one, the monthly reanalysis global atmospheric circulation data provided by ERA5 includes average evaporation rate, average total precipitation rate, zonal wind, meridional wind, vertical velocity, and specific humidity data; the download address for the monthly reanalysis global atmospheric circulation data provided by ERA5 is: https: / / cds.climate.copernicus.eu / datasets; the download address for the sea surface temperature reanalysis dataset provided by ERSST V5 is: https: / / www1.ncdc.noaa.gov / pub / data / cmb / ersst / v5 / netcdf / .

3. The method according to claim 1, characterized in that, In step two, the present invention uses monthly reanalysis global atmospheric circulation data provided by ERA5 to calculate the precipitation index of Central America in spring and summer; spring refers to March to May, and summer refers to June to September.

4. The method according to claim 1, characterized in that, In step two, the Central America Precipitation Index is defined as the average precipitation anomaly in the regions of 7°N-22.5°N and 80°W-100°W.

5. The method according to claim 1, characterized in that, In step three, the formula for calculating the precipitation phase transition index is: Precipitation Phase Transition Index = Cor all -Cor Rem (t) (1; In formula (1), Cor all To investigate the correlation between the precipitation index in Central America during spring and summer over a specific period; Cor Rem (t) is defined as the correlation coefficient between the spring and summer precipitation indices of Central America after year t, without considering the subsequent years.

6. The method according to claim 1, characterized in that, In step three, the determination of transitional events and persistent events is based on the numerical value of the precipitation phase transition index, which classifies spring and summer precipitation anomalies in Central America into transitional events and persistent events. The persistent event is an event with a precipitation phase transition index greater than 0, and the transitional event is an event with a precipitation phase transition index less than 0.

7. The method according to claim 1, characterized in that, In step four, a positive event refers to an event in which the spring precipitation index of Central America is greater than 0 in a persistent event; a negative event refers to an event in which the spring precipitation index of Central America is less than 0 in a persistent event; the evolution of the transitional event and the persistent event is related to the evolution of the vertically integrated water vapor flux and vertical velocity.

8. The method according to claim 1, characterized in that, In step five, the expression for the water vapor budget equation is: （2）； In formula (2), These represent outliers in precipitation. This represents the contribution of local evaporation to precipitation anomalies; Represents the horizontal thermal term; Represents the horizontal dynamic term; NL represents the vertical thermal term; NL represents the nonlinear term. Representing the vertical dynamic term, its physical meaning is: the vertical transport of climatological relative humidity caused by abnormal vertical motion; among which, Outliers representing vertical velocity The climatological average value of vertical velocity during the study period; The vertical gradient representing the climatological average relative humidity; Represents the vertical gradient of relative humidity relative to climatological anomalies; < > is: , representing the vertical integral from 1000 hPa at the Earth's surface to 300 hPa at the tropopause; g represents the gravitational acceleration, chosen as 9.8 m / s². 2 ; The climatological average value of the horizontal wind field during the study period; This represents anomalies in the horizontal wind field relative to the climatological state. The horizontal gradient representing relative humidity relative to climatological anomalies; The horizontal gradient represents the climatological average relative humidity.

9. The method according to claim 1, characterized in that, In step six, the key sea surface temperature regions are the tropical central and eastern Pacific Ocean and the tropical North Atlantic Ocean; the method also includes: using synthetic analysis to reveal the key tropical ocean sea surface temperature anomaly regions that regulate spring and summer precipitation anomalies in Central America during persistent and transitional events, and defining a sea surface temperature index based on the key sea surface temperature anomaly regions.

10. The method according to claim 9, characterized in that, In step seven, the method includes: based on the defined sea surface temperature index, combined with correlation analysis and partial correlation analysis, revealing the impact of tropical ocean sea surface temperature anomalies on precipitation anomalies in Central America.

11. The method according to claim 1, characterized in that, In step eight, the method includes: based on the defined key sea surface temperature zones and combined with regression analysis, revealing the physical processes by which tropical ocean sea surface temperature anomalies affect precipitation anomalies in Central America.

12. The method according to claim 1, characterized in that, In step nine, the method includes: using synthetic analysis to reveal tropical ocean surface temperature anomalies during winter preceding transitional and persistent events.

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